Protein tyrosine kinase 7 promotes PI3K/AKT signaling and survival in primary and neoplastic CD4+ T-lineage cells. (HEM4P.231)
Bibliographic record
Abstract
Abstract Protein tyrosine kinase 7 (PTK7), a catalytically inactive receptor tyrosine kinase (RTK) that is highly expressed in intrathymic development, is a novel marker for human CD4+ recent thymic emigrants (RTEs), and is also highly expressed on some T-lineage thymomas, e.g., Jurkat cells. The function of PTK7 in normal human T-cell development and tumors remains unclear. Here, using RNAi-mediated gene silencing in T-lineage tumor cells, primary human peripheral T-cells and thymocytes, we found that targeting PTK7 consistently decreased cell survival by augmenting caspase-3 activation of apoptosis. The PTK7 knockdown also decreased AKT phosphorylation and PI3 kinase activity, suggesting an essential role for PTK7 in survival of RTEs and developing thymocytes involving the PI3K/AKT pathway. Using mass spectrometry of we identified insulin-like growth factor-1 (IGF-1) receptor as an active kinase partner of PTK7. Knockdown of PTK7 reduced IGF-1 receptor function in primary T-lineage cells, confirming the biologic importance of this physical association. This role for PTK7 in promoting cell survival via its effects on cell survival via the PI3K/AKT pathway may not only be relevant to normal T-cell development, including the RTE compartment, but also to the oncogenesis of T-lineage and epithelial cell tumors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".